116 citations · 134 across the 4 of their papers we have counts for
9 papers
User-Level Membership Inference Attack against Metric Embedding Learning
Guoyao Li, Shahbaz Rezaei, Xin Liu
Membership inference (MI) determines if a sample was part of a victim model training set. Recent development of MI attacks focus on record-level membership inference which limits t…
An Efficient Subpopulation-based Membership Inference Attack
Shahbaz Rezaei, Xin Liu
Membership inference attacks allow a malicious entity to predict whether a sample is used during training of a victim model or not. State-of-the-art membership inference attacks ha…
On the Difficulty of Membership Inference Attacks
Shahbaz Rezaei, Xin Liu
Recent studies propose membership inference (MI) attacks on deep models, where the goal is to infer if a sample has been used in the training process. Despite their apparent succes…
Security of Deep Learning Methodologies: Challenges and Opportunities
Shahbaz Rezaei, Xin Liu
Despite the plethora of studies about security vulnerabilities and defenses of deep learning models, security aspects of deep learning methodologies, such as transfer learning, hav…
Large-scale Mobile App Identification Using Deep Learning
Shahbaz Rezaei, Bryce Kroencke, Xin Liu
Many network services and tools (e.g. network monitors, malware-detection systems, routing and billing policy enforcement modules in ISPs) depend on identifying the type of traffic…
Multitask Learning for Network Traffic Classification
Shahbaz Rezaei, Xin Liu
Traffic classification has various applications in today's Internet, from resource allocation, billing and QoS purposes in ISPs to firewall and malware detection in clients. Classi…